Rainfall deciles for April-September. From http://www.bom.gov.au/climate/maps/

If you live in NSW, you might have noticed it’s been pretty dry lately. In Sydney we’ve had our driest September on record, and the last time we had real rain was two whole months ago, the longest spell on record. After a very wet March, April-September has been the driest for Sydney in over a decade.

In the absence of El Niño, we look to other explanations, like the very high pressure in June. And for the east coast, it feels like we just haven’t had any ECLs. But is that true?

Conveniently, NCEP in the USA provides grids of “reanalysis” pressure data almost in real time, so I ran my tracking scheme and had a look! During April-September, which is the main ECL season (as well as the period it’s been so dry), typically there are 28 days with a low pressure system somewhere in the ECL region. This year there were 24 – not that much different to normal.

All cyclones April-September 2017. Crosses mark strong systems

I know what you’re thinking – you would remember if that had happened! As it turns out, our standard ECL box extends pretty far east, and this year the systems were generally too far east (or south) to affect the coast.

Only 12 days this year had an system closer to the coast, the fewest since 2003. And only five were north of 38°S, the main one being a pretty weak low on the coast that contributed to rain during early June.

In fact, they were all pretty weak. Only four days had an ECL reach a strong threshold anywhere in the domain, and just one in the closer region (and it was very far south).

Usually there are 12 days with a strong ECL; last year there were 18 days, including 15 with a strong ECL near the coast and a pretty severe one in June! Amusingly, this means that while this year had the fewest strong ECLs since 1994, last year had the most since 1990, really showcasing how variable ECLs are!

Number of April-September ECLs from the NCEP reanalysis.

But why?

Well, I'd like to tell you. Unfortunately, we actually don't have a very good understanding of why and how ECLs vary from year to year. There's some evidence that they're more likely in La Niña years, especially the ones with very heavy rain and flooding - but generally their relationship with the big climate drivers is pretty weak, with some very significant ECLs during big El Niño years like 2015.

While there is some relationship with changes in pressure patterns such as SAM, this year hasn't been that much different to the last couple, which had heaps of ECLs. And that really high pressure from June didn't really continue into the rest of winter.

So I actually have no idea. It could just be random chance, or maybe there are climate patterns we just don't understand yet. But it would be an interesting thing to know!

I was lucky enough to have two papers published in the last month. The second was the final part of my PhD, so publishing this paper is the real end of my studies. It’s also probably the most challenging paper I wrote, so I thought I would talk about the process a bit.

A long journey

From the beginning, understanding the relationship between ECLs and the Great Dividing Range next to the coast was going to be one of the major points of my PhD. My first model simulations were done three years ago, when I was playing with changing topography for a single month in my regional model, and my first presentation about it was all the way back in June 2015.

So why did it take so long to publish anything? Part of it was getting distracted by other shiny things to study, but it was also due to my growing understanding of what we should and shouldn’t do with regional models - that is, models that are run at high resolutions but over small areas of the globe.

My early simulations were for a single month, which doesn’t really tell you much about changes in the frequency of ECLs. So the next step was running the model over 2 years, just like I did with changes in sea surface temperatures. But after doing all that, I got asked some really important questions by my supervisors.

Simply, what I had been doing for sea surface temperatures was “nudging” the model fields in the upper atmosphere to be more like the global observations. This is good to make sure the broader atmosphere is the same, so we can compare individual events. But unlike oceans, mountains extend well up into the atmosphere, which means that this “nudging” is actually stopping the model from properly incorporating the changes.

So, more model simulations, that had to run for a lot longer. As part of this, I made a mistake setting up one of my model simulations which I didn't realise til it was done, so I had to do it all over again, wasting another month.

… about a month before I got my thesis results, the paper was rejected. :(

It was too messy - I had tried to include all my different types of simulations, and the results just weren’t very clear. In the end I had to throw out almost everything - all of those 2-year simulations, the extra runs I did because I had started them wrong, everything except a couple of my long simulations. All those thousands of hours of supercomputer time and countless hours of analysis, for nothing. It was quite depressing, especially since I hadn’t had a rejected paper in half a decade.

But I got over my sadness and rewrote the whole paper from scratch, to create something much clearer. It was hard, but worth it when I resubmitted and the reviewers accepted it with only minor comments. Hooray!

So, what’s the moral of the story?

Put more thought in the best way to do your model simulations before you start, so you don’t have to redo them all

Just because you spent a lot of time on something, doesn’t mean it should be in the paper. Learn to let go

As always, academia is about persistence. It may feel depressing when a paper gets rejected, but it’s not a reflection on you and there’s always another chance

But what was the paper about?

Climate models tend not to have enough ECLs near the coast, so I wanted to know how important the Great Dividing Range is, since it basically doesn’t exist in a global model that has 200 km between points. So I ran my regional model over Australia & surrounds with the height of all the land set to 0m.

And what did I find? Topography actually isn’t as important as everyone thought. Removing it means we get fewer ECLs coming from the Bass Strait, especially in spring, but the number that form near the coast actually increases! There’s also no change in the number of strong events, although the wind speeds and rain on the coast are lower because they’re not being forced up by the mountains.

Change in average rain rate and wind speed for ECLs within 500km from the coast when topography is removed. Plot shows a radius of 500km from the centre and is oriented so north is at the top

That seems like a lot of work for not much result, but it’s actually quite important to know that we shouldn’t focus so much on the Great Dividing Range when it comes to ECLs - it’s much less important than the warm oceans near the coast. So future scientists (or future me) can move on to other questions, like what would happen if we wiped out New Zealand? I think that would be super interesting!

It's been a while since I wrote a blog, but it's always good to talk about new research. In the limbo stage between finishing my PhD and finding a job, one of my supervisors luckily had the funds to employ me as a research assistant for a few months, where I worked on this project. I started work on it at the end of January, so it's pretty cool that it's published online already!

Example of what an average ECL looks like from reanalysis pressure data

One of the things I've mentioned before is that there's no perfect database of past East Coast Lows, which would be a handy thing to have to look at things like trends, variability, or whether climate models do a good job. The main way we identify ECLs is by taking computer code that's good at identifying areas of low pressure, and applying it to some sort of gridded pressure data.Since we can't get gridded pressure observations from satellites, what we use are called reanalyses. These are basically a weather forecast model that takes in all of the observations from around the world to make the best possible guess of what the atmosphere currently looks like.

Average ECL wind pattern from satellite data

There are about half a dozen of these reanalyses, and they all use different models. And the tricky thing is that if you smooth them all out to the same resolution - about 250 km between each grid point - they all kinda show the same results when you look for ECLs using your algorithm. But when you use grids that are more like 50 km instead, some reanalyses seem to have more than double the number of cyclones that others do!

So this paper is an attempt to see which reanalysis is actually the most correct, using satellite data. Because while we don't have global observations of pressure, we do have satellite observations of rainfall and winds. And we know that a "cyclone" should have "cyclonic" winds - which in the southern hemisphere basically means clockwise, spiraling into that central low point. So we took the satellite winds for a database of "known" ECLs to find some parameters that an ECL should have, and then looked at what the satellite winds showed for a whole bunch of reanalyses.

What we found was that there was a really simple metric we could use to check if an identified ECL was a "real" cyclone with cyclonic winds, and using this made the reanalyses a lot more similar. The one reanalysis that had too many ECLs, had a lot of systems which weren't really cyclones, and looked a lot more like a cold front. Conveniently, the "best" reanalysis for ECLs was the European one, which is already the most popular for ECL studies. This helps us get a better handle on which dataset to use for evaluating climate models.

Last month, a severe extratropical cyclone hit southeast Australia, which is being called a 1-in-50 years event. The storm caused severe winds, heavy rainfall, and major damage, including a blackout that affected the whole state of South Australia.

So, how do we know it was a 1-in-50 year storm, and how can we tell how strong a cyclone is in general? Tropical cyclones have a cyclone intensity scale we talk about, and people have some idea of the difference between a category 1, 3 or 5 cyclone. This is based on the strongest winds around the cyclone centre, which isn’t always a perfect indicator of how large its impacts are.

But what about extratropical cyclones, like the one that hit Adelaide, or the East Coast Lows that I study? They can be a bit harder to pin down.

1. Central pressure

One of the easiest ways to think about how strong a cyclone is is the pressure in the middle of a cyclone, with deeper cyclones being stronger. During the Adelaide cyclone, Bureau mean sea level pressure charts gave it a minimum central pressure of 973.3 hPa, which sounds pretty low.

Mean Sea Level Pressure chart for 1600EST on 28 September 2016. All pressure charts are from the Australian Bureau of Meteorology

MSLP chart for 1600 EST 22 April 2015

Of course, we don’t have good databases of cyclones in southern Australia to compare this easily to past events, so we have to make one. To do that, I ran the same cyclone tracking method I use for ECLs, but changed the region I was looking at to cover the Adelaide region - 25-45°S, 125-145°E. I ran this on gridded pressure data from the NCEP1 reanalysis, which allows us to look at cyclones back to 1948, although it’s important to note there might be some issues in the pressure data, especially before satellites came in in 1979.

Because the reanalysis only has pressure data every 250 km, the central pressure of the cyclone wasn’t as strong - 977.7 hPa. But this was the deepest cyclone in the analysis north of 37.5°S, which ties in pretty well to the 1-in-50 years claim. Deeper cyclones are more likely to be further south - some cyclones around Antarctica in my dataset had pressures down to 930 hPa!

2. Pressure gradients

The problem with using the central pressure of the cyclone is that pressure tends to get lower as you move south. This means that central pressure really isn’t a good indicator of how bad a cyclone’s impacts are, especially for East Coast Lows. The complex ECL that caused a lot of damage in June this year had a central pressure of 990 hPa; the severe ECL from April 2015 only got down to 1007 hPa.

So a more common way scientists will look at cyclone intensity is by looking at how strong the gradient of pressure is, which is a better indicator of how strong the winds will be. This can be measured in a number of ways, including by looking at the average difference in the pressure between the cyclone centre and the pressure 200km or 500km away, or by calculating metrics like the “Laplacian” of pressure (which is what my method uses).

Using this method, I get a Laplacian for the Adelaide cyclone of 3.5, which is way higher than the previous record for this far north in the Adelaide area of 2.9. This is also stronger than any of the ECLs in my database, although there have been a few with intensities stronger than 3, most recently in June 1998.

Of course, this is usually calculated as an average around the cyclone - ECLs often have much stronger gradients to the south of the cyclone than the north, so you may want to only calculate the maximum pressure gradient of the storm, or the gradient on the south side, to really get at those big events. And low-resolution pressure fields like in the NCEP reanalysis really can’t capture the smaller “mesolows” that cause locally severe impacts inside the bigger system. So the Laplacian for the April 2015 ECL is only 1.4, and the infamous Pasha Bulker storm is only 1.6.

3. Impacts

What people really care about with cyclones are the impacts - how strong was the wind, how much rain fell, how big were the waves? This can be influenced by a number of things beyond the cyclone itself, like how high the astronomical tides are or how warm/moist the atmosphere is (both important for the ECL in June 2016). It can also depend on other things like how big the cyclone is, how close it is to populated areas, or how long it stays in one place. These are even harder to quantify, although there is a good analysis looking at severe ECLs in terms of their coastal flooding.

Because the storm in September was that bit further north, it was in just the right place to have major impacts, with very strong winds and many September rainfall records. A few degrees further south, and you have the cyclones that passed through on 10 July and 18 August this year - South Australia still received strong winds and rain from the cold fronts attached, but the impacts were much smaller.

MSLP chart for 1600EST on 18 August 2016

So really, whatever way you look at it, the cyclone in South Australia last month looks like the strongest in the area for at least 60 years. But it’s not always as simple, especially when dealing with ECLs.

It’s been another cold, wet couple of days, courtesy of another East Coast Low. It certainly feels like there have been a lot of East Coast Lows lately, but have there really?

How often do ECLs happen anyway?

As I’ve mentioned before, the question depends a bit on how you’re defining ECLs.

Taking the widely-used ECL database by Speer et al. (2009), there are about 7 ECLs per year that have widespread coastal rain, varying from just 3 in 2000 & 1980 to 14 in 1978 and 1988. In Sydney, of the four days a year with 50 mm of rain or more, about half of them are due to ECLs, including 6 ECL-related heavy rain days in 1998.

While on average one ECL a year causes widespread coastal flooding, about half the years between 1860 and 2014 had no ECL-related severe flooding, while there were 5 big ECL floods in 1879 and 1975.

The important ECLs also often come in clumps, when the conditions are right for several ECLs to happen in the space of a month or two. This happened in June 2007, April 2015 and June 2016, but is not a new phenomenon – in fact, 42% of significant ECLs occurred in a group of at least 3 ECLs over 2 months, including 56% of events in those main months of April-June.

How do recent years compare?

The first decade of the 2000s had slightly lower ECL frequencies using some definitions, but most studies find no real trends in ECL frequency over at least the last 60 years, while coastal floods have increased in frequency over the last century.

As a scientist it’s tricky to compare years when the data isn’t in yet – automated ECL methods generally rely on reanalysis data, which is currently only available until March this year. And the reanalyses aren’t perfect, especially with the small/complex ECLs that can still do a lot of damage – for example, the severe ECL from April last year wasn't very symmetrical, so doesn't show up very well in reanalysis data.

21 April 2016 - BoM Chart

21 April 2016 - NCEP Reanalysis

Looking through the Bureau’s archive of weather maps and ﻿reports﻿, this year has so far seen at least 5 major ECLs – one in January, two in June, one in July, and now one in August. And, of course, many other lows that were smaller, or less impactful, or a bit further away from the coast. So far that seems about normal to me.

Perhaps the feeling that there are more ECLs than usual is just short-term memory and too much Sydney focus – yeah, we’ve had some big ECLs in 2015 and 2016, but in terms of history it’s really not that exceptional. Just in the last 30 years there have been 21 ECLs that caused at least 100mm of rain in a day in Sydney, including three in 1998 and a massive 328 mm in 1986, and there have been some much more severe ECLs in the past. But just one of these Sydney ECLs was in the seven years 2008-2014 and it was pretty shortlived, so it’s been a while.

There's a huge amount of year to year variability in ECLs, and there’s a lot we still don’t know about how much they've varied in the past. But to look at the last couple of years and think ECLs have increased in frequency is probably a tad precipitous.

Every time an East Coast Low hits, people ask whether they are getting more frequent. But this is a hard question to answer, as there is relatively little pressure data available before the 1950s, making it hard to identify long-term changes in frequencies. So far, limited studies suggest southeast Australia may have become less stormy compared to the 19th century and earlier periods:

Paleoclimate data suggests that the climate of eastern Australia was much stormier during the 1600s to 1900s than now

All of these studies looked at slightly different things, so results can't necessarily be applied to East Coast Lows as I've been defining them. But the lack of station data before 1950 means that the maps of pressure we use to find ECLs (mostly from products called reanalyses) don't start until the 1950s or even 1979 (when satellite data is available). So, what can we do?

Last year, we had a student from the US visiting us during the winter, and we decided to look at whether we could say anything about ECLs using the 20th Century Reanalysis, which goes back to the late 1800s. What makes this reanalysis special is that instead of having just one version, they ran it 56 times with different initial conditions, just like we would do for modern seasonal prediction - we call this an ensemble. This means we can get a more robust look at different ways the climate might have been during the past, when our observations were less useful.

We found that, prior to around 1960, the different ensemble members did different things, so if you used the average pressure field you found very few ECLs at all. But, if you look at ECLs in each of the members individually, there was a lot of agreement on how many ECLs occurred each year, at least back to about 1910, beyond which things start to get a bit sketchier. We also found the ensemble members did a surprisingly good job of detecting the really big and impactful ECLs during the late 1800s, which made us confident they were identifying “real” cyclones.

Boxplots show the numbers of ECLs per decade across all the 56 20CR ensemble members, and crosses indicate the frequency in the 20CR ensemble mean. In the later decades, triangles indicate frequencies in ERAI, one of the best of the "modern" reanalyses

This helped us extend our records of ECL frequency back to at least 1910, from which we can say:

There has been no significant long-term trend in ECL frequency in the last 100 years;

But the decade 2000-2009 had the lowest frequency of ECLs in at least the last century

As for whether the current decade has had above or below ECL frequency? Well, we'll have to wait and see what the rest of the decade brings.

This weekend, an East Coast Low (ECL, also known as an East Coast Cyclone) has been ravaging the east coast of Australia, causing very heavy rain, flooding, strong winds, rough seas, and coastal erosion. These sorts of storms are not uncommon – there were at least four East Coast Lows that caused major impacts last year, including a very severe ECL that hit Sydney and the Hunter in mid-April, while June 2007 had five East Coast Lows in a single month.

However, when people start asking questions like, “How often do these storms happen?” or “How does La Niña influence East Coast Lows?”, the answers aren’t quite as simple as you might think. Quite simply, there is still a lot of uncertainty on what actually makes an East Coast Low.

There are some East Coast Lows that everyone can agree on, like the Pasha Bulker storm of 2007 or the Sygna storm of 1974. These storms tend to have the following characteristics:

A closed low pressure system on the surface

Forms or intensifies directly near the east coast (this can be very rapid, a so-called “explosive” cyclone or “bomb”)

Has some component of movement parallel to the coast

Very severe weather, particularly on the south side of the low

A “cold pool” or low in the upper atmosphere

But when trying to put together a database of events for science and analysis, it starts to get trickier, and more questions arise.

Where do you draw the line?

Is it still an East Coast Low if there is a surface cyclone, but there isn’t any severe weather?

The most widely cited database of cyclones, by Speer et al. (2009), defined cyclone based on how they looked on a weather map. Using that approach, there are about 22 ECLs a year, but only 7-8 have widespread rain and 2-3 have “explosive” development. In contrast, work by Jeff Callaghan and Scott Power started by looking at storms with big impacts on the coast, and then tried to see what systems caused them. Both these approaches have value, but they give you very different databases.

Is the surface low the most important part?

We know that how strong the low pressure system looks on the weather map isn’t really a good indicator of how big its impacts are – if you look at all the maps for all ECLs in June 2007, you wouldn’t necessarily guess that the most impactful one was 7-8 June. So some studies just look at the upper level circulation instead of the surface low, as that might be a better guide to impacts.

How can a computer best identify cyclones?

Looking through weather maps is hard and time-consuming, so we need a better way to get databases of cyclones. There are a lot of different automated methods these days for identifying cyclones from gridded pressure data. But they all identify ﻿slightly different systems﻿, and they also depend on which pressure data you use. This can mean some quite large differences between automated databases in identifying smaller or less severe systems, and mean you get very different correlations between ECL frequency and things like El Niño and La Niña. Annoying.

How close to the coast does an ECL need to be?

The Speer et al. (2009) database looked at cyclones anywhere from the coast to 160° E, but the most impactful cyclones occur much closer to the coast. On the other hand, a very large cyclone could have impacts further from the low centre, and a very restrictive definition might mean important cyclones get missed. Where do you draw the line? Current definitions also tend to look at cyclones between Gippsland and Fraser Island – but what about cyclones in the Bass Strait, such as during the infamous Sydney-Hobart race of 1998, or near Tasmania?

What about the “type” of ECL?

East Coast Low is a funny category, and often lumps together very different types of systems – big extratropical cyclones that come from the westerlies to the south of Australia, ex-Tropical Cyclones that come from the north, cyclones that develop in a trough right along the east coast. All of these systems can have quite different characteristics and impacts, as well as different relationships with things like La Niña. But there are a lot of differentclassifications used by different groups, and it can be difficult to apply them in an automated way, so lazy people like me often lump all the storms together. This makes analysis easier, but may lose some of the fine detail we need to understand cyclones properly.

Ultimately, it’s all a bit subjective, and every study uses a slightly different definition. So, if you ask me “How often do storms like this happen?” or “Does La Niña mean we’ll get more storms like this this year?”, at the moment my answer is “Well, it really depends on what you mean by East Coast Low…”

One of the things I'd like to get better at is using this blog to promote/discuss recent research I've published. So, today I'm going to talk about a paper I have in press at GRL.

As I've spoken about before, East Coast Lows are one of the main causes of severe weather along the east coast of Australia, as well as being very important to our long-term water security. So there is a lot of interest in whether these storms will change with global warming over the coming century. Broad-scale study of storm tracks across the globe, as well as recent work looking at ECL-favourable conditions in the upper atmosphere, suggest that they will probably decrease in frequency.

But these studies all focused on the big picture, and haven't looked at how the individual storms will change, especially the small and short-lived storms that can develop overnight. My paper is different in a couple of ways:

Instead of global climate models, I used regional climate models, which give higher-resolution data and are better able to identify individual lows

Instead of just one method of tracking cyclones, I used three, at multiple resolutions - this is important because all computer programs to identify cyclones identify slightly different things

I used two methods that identify individual cyclones, making it possible to look at changes in the location and impacts of cyclones for the first time

So, what were my results?

Winter ECLs are likely to decrease in the future, consistent with previous studies

There are larger uncertainties for summer ECLs and ECLs close to the coast - these may actually become MORE frequent

Even though winter cyclones are likely to decline, there may be an increase in cyclones with heavy rain in both seasons

% Change in ECL frequency in 2060-2079 compared to 1990-2009 in May-October and November-April. Crosses indicate areas where the sign of the change is consistent across 75% of members

What's next?The regional models still had issues with getting the correct seasonality of ECLs, and I want to increase our understanding of why the models do what they do:

Could the different changes along the coast be related to the impact of the East Australian Current? How does it influence cyclones anyway?

Why are the trends different in the different seasons - is it related to different types of ECLs?

Why do the models have too few cyclones in the cool season and directly near the coast - could it be something wrong in the topography?

To improve our understanding of these, I'm doing my own model runs, to get into the details of how ECLs work.

What is an East Coast Low?In some ways, an ECL is easy to describe - it's a low pressure system that occurs off the east coast of Australia, generally defined between Brisbane and eastern Victoria. Low pressure systems, of course, happen around the world and are a major cause of weather everywhere, although we get a bit more than normal for our latitude. A few years back, a study by Speer et al. (2009) found that there are about 22 ECLs a year, of which about 7 cause widespread rainfall totals above 25 mm. They're most common in winter, especially in May and June, but can happen any time of year.But, as always in science, it gets a bit more complicated than that. Because there are a lot of different things that sometimes get included under the term “East Coast Low” that look quite different to each other, leading to a lot of disagreement on what exactly distinguishes it from any other low. See how different the five ECLs in June 2007 alone looked! So a big low pressure system that comes from the westerly storm track south of Australia, or an ex-tropical cyclone, or a small but intense low that develops in a coastal trough, could all be included under some definitions, and excluded under others.And then you get into all the different computer-based methods for finding ECLs (none of which do exactly the same thing as human pattern recognition) and different sets of pressure data to find them in, and… you can see how it gets complicated. (We recently published a whole paper comparing different computer-based methods and how their “ECLs” compare with those that Speer et al. found)So, this means that we can never truly answer the question of “How many ECLs are there each year” – it always depends on what you mean by ECL!

Why do I study ECLs? In a way I fell into studying ECLs by chance – back when I was doing my masters (in polarimetric radar, a very different thing), I got a part-time job at the Bureau of Meteorology, and the first project I worked on was helping with the Speer et al. paper (making it my first paper!). At that time, ECLs were suddenly a hot topic of research in NSW, having had a very significant ECL in June 2007 that people are still talking about, thanks to a ship (the Pasha Bulker) that got stuck on a beach just north of Sydney. And thanks to the vagaries of geography, most of the climate researchers in Australia were based in Melbourne and focusing on droughts, leaving the climate of the east coast as fair game for a young, up & coming researcher.So, since I was based in Sydney, I just started playing with bits and pieces of projects on east coast climate, with a particular focus on ECLs, since they turned out to be one of the biggest causes of severe weather in our region as well as critically important to our dam levels (if you look at a chart of Sydney dam levels you can really see June 2007’s impact!)This lead to being involved in a multi-agency/university partnership known as ESCCI, where I met the people who would become my PhD supervisors. As to what I’m actually doing in my PhD? That can wait til next time.

Update: Wow, apparently this got some traction! Thanks everyone who was interested - an improved version of this (with less focus on me) is now available here.

The current BoM forecast for 10am on 21 April

Well it's a miserable day in Sydney today, and set to get worse tomorrow as an East Coast Low develops, likely the biggest one since spring last year. So this seems as good a time as any to start my 2015 goal of occasional blogging, starting with the question – what is an East Coast Low, and how did I come to study them?

Author

This is where I will try to discuss a little bit about my research and science I find interesting.

My views are my own, and do not represent either UNSW or the Bureau of Meteorology